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scikit-learn Cookbook , Second Edition

You're reading from scikit-learn Cookbook , Second Edition Over 80 recipes for machine learning in Python with scikit-learn

Product type Paperback

Published in Nov 2017

Publisher Packt

ISBN-13 9781787286382

Length 374 pages

Edition 2nd Edition

Languages

Python

Tools

Scikit-learn

Concepts

Machine Learning

Author (1):

Trent Hauck

View More author details

Table of Contents (19) Chapters

Title Page

Credits

About the Authors

About the Reviewer

www.PacktPub.com

Customer Feedback

Preface

1. High-Performance Machine Learning – NumPy FREE CHAPTER

2. Pre-Model Workflow and Pre-Processing

3. Dimensionality Reduction

4. Linear Models with scikit-learn

5. Linear Models – Logistic Regression

6. Building Models with Distance Metrics

7. Cross-Validation and Post-Model Workflow

8. Support Vector Machines

9. Tree Algorithms and Ensembles

10. Text and Multiclass Classification with scikit-learn

11. Neural Networks

12. Create a Simple Estimator

Looking at the UCI Pima Indians dataset web page

We did some exploratory analysis to get a rough understanding of the data. Now we will read the UCI Pima Indians dataset documentation.

How to do it...

View the citation policy

Go to https://archive.ics.uci.edu/ml/datasets/pima+indians+diabetes.
Here is all the information about the UCI Pima Indians diabetes dataset. First, scroll down to the bottom of the page and look at their citation policy. The diabetes dataset has the general UCI citation policy available at; https://archive.ics.uci.edu/ml/citation_policy.html.

The general policy says that to publish material using the dataset, please cite the UCI repository.

Read about missing values and context

The top of the page has important links and an abstract of the dataset. The abstract mentions there are missing values in the dataset:

Below the abstract, there is a description of the attributes (this is how I came up with the names for the columns at the beginning):

What do the class variables mean...

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Authors (1)

Trent Hauck

Trent Hauck

Trent Hauck is a data scientist living and working in the Seattle area. He grew up in Wichita, Kansas and received his undergraduate and graduate degrees from the University of Kansas. He is the author of the book Instant Data Intensive Apps with pandas How-to, Packt Publishing—a book that can get you up to speed quickly with pandas and other associated technologies.

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